Realistic chipless RFID : identification and localization

For mass deployment of RFID systems, cheap and accurate item level identification and tracking are profoundly needed. Fortunately, unlike conventional chip-based RFID, chipless RFID systems offers low-cost printable tags holding a better chance to enter the era of penny-cost tags.
This dissertation concentrated on solving three challenges in the detection of the chipless tag inside an indoor environment. The first aspect discussed in the thesis are the chipless RFID clutter removal techniques. In chipless RFID the environmental clutter response is defined as the signal reflected from the environment, that does not interact with the tag. This signal has higher power than the backscattered signal from the tag, rendering the tag signature undetectable. Two algorithms to overcome this problem was used, the first is empty room calibration. The first algorithm is based on subtracting the measurement with the tag from the one without. The second algorithm is Rake receiver using PN sequence; this algorithm requires no pre-measurement calibration.
The second aspect is notch detection and identification which is a critical part of the chipless system. This part is responsible for converting the notches into bits. For effective detection, a windowing operation is proposed, where each window may contain a notch or not. Three novel techniques are implemented to detect the notch. The first is matched filter were a reference notch is compared with the incoming signal. The second is window based singular value decomposition, where a constellation is created to detect not only the existence of a notch but also the bandwidth of the notch. The third notch detection technique is dynamic frequency warping. This technique utilizes non-linear warping to detect the notch and the frequency shifts that occurs on the notch.
The third aspect discussed in the thesis is tag localization. In this aspect, two algorithms are implemented and explained. The first is trilateration which requires three different readers. The second localization algorithm exploits received signal strength and angle of arrival to detect the location of the tag accurately. All the algorithms were tested using a real testbed to validate the reliability of the techniques.
The measurements were done using fabricated tags in an indoor environment using Software Defines Radio (SDR).

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